The present invention applies to communications systems, all of which are inherently limited in their capacity (or rate) of information transfer by channel impairments. One example of an impairment is often referred to by the generic term “noise.” Noise sometimes emanates, for example, from within electrical components themselves, such as amplifiers and even passive resistors. Another example of an impairment is referred to as “interference,” which is usually taken to be some unwanted manmade emission perhaps for another communications system such as radio, or perhaps from switching circuits in a home or automobile. “Distortion” is a further example of an impairment, and includes linear distortion in the channel, such as pass-band ripple or non-flat group delay, and nonlinear distortion, such as compression in an overdriven amplifier. Of course, there are many other types of impairments that may adversely affect communications in a channel.
Often in communications channels, the impairments may by dynamic in nature. In many cases, the impairment level may be at one level of severity most of the time, and the communications system may be designed or optimized (in some fashion) to operate at that level of impairment. Occasionally, however, one or more of the impairments may rise to so severe an amount as to preclude the operation of the communications system optimized for the more ordinary level of impairments.
In prior art, in some applications where a large interferer or burst of noise occasionally impinges upon the receiver, the received signal is simply blanked during increased power to mitigate large out-of-the ordinary bursts of received power. Often, analog processing means are used, almost at, if not right at, the receiver input. Sometimes this is done especially to protect sensitive receiver front-ends from damage. While this technique may provide some benefit in circumstances where the noise or interference power dwarfs the signal-of-interest power, it does not protect against the many other impairments which have power more on the order of the signal-of-interest power (or even much less). Also, by itself, this blanking does not provide the receiver with a means to improve its overall performance in the presence of the lost information, i.e., the information content concurrent with the large noise burst.
Other prior art that may have been applied to this problem, even unknowingly, is the use of forward error correction (FEC) techniques that incorporate soft-decision decoding, such as is common with convolutional error correction codes and the Viterbi decoding algorithm. In this prior art, as the error power in the received signal is increased, this increase is passed directly into the decision process. Such encoding and decoding techniques have been in common practice for years, and are widely applied without thought to temporary fidelity changes in the channel. Fortunately, in the event of a change in the channel fidelity, the soft-decision decoding will automatically take into consideration the larger error power in making signal decisions. However, unfortunately, often with a change in channel conditions, there is a duration of multiple symbol intervals (in a digital communications system example) where the degradation persists, and during this time some symbols may be erred so severely that they actually appear close to another possible (but wrong) symbol. In this event, which becomes much more likely as the constellation density (of a QAM constellation, for example) is increased for high rate communications, the soft-decision decoder actually “thinks” it has received a low error power, and may rate the wrong signal with a high confidence.
Further limitations and disadvantages of conventional and traditional approaches will become apparent to one of skill in the art, through comparison of such systems with the present invention as set forth in the remainder of the present application with reference to the drawings.